{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/45170"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/45170","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Quality of care and drug surveillance : a data-driven perspective","abstract":"In this thesis, we describe the use of medical insurance claims data in three important areas of medicine. First, we develop expert- trained statistical models of quality of care based on variables derived from insurance claims. Such models can be used to identify patients who are receiving poor care so that interventions can be arranged to improve their care. Second, we develop an algorithm that utilizes claims data to perform post-marketing surveillance of drugs to detect previously unknown side effects. The algorithm performed strongly in several realistic simulation tests, detecting side effects a large fraction of the time while controlling the false detection rate. Lastly, we use insurance claims data to improve our understanding of the costs of care for patients who suffer from depression and a chronic disease.","abstract_html":"In this thesis, we describe the use of medical insurance claims data in three important areas of medicine. First, we develop expert- trained statistical models of quality of care based on variables derived from insurance claims. Such models can be used to identify patients who are receiving poor care so that interventions can be arranged to improve their care. Second, we develop an algorithm that utilizes claims data to perform post-marketing surveillance of drugs to detect previously unknown side effects. The algorithm performed strongly in several realistic simulation tests, detecting side effects a large fraction of the time while controlling the false detection rate. Lastly, we use insurance claims data to improve our understanding of the costs of care for patients who suffer from depression and a chronic disease.","abstract_has_math":false,"creators":["Czerwinski, David (David E.)"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Physics.","school":null,"contributors":[],"advisors":["Dimitris J. Bertsimas."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:21:19Z","subjects":["Physics."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/45170","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Dimitris J. Bertsimas."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Physics."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Dept. of Physics."]},{"key":"dc:creator","label":"Author","values":["Czerwinski, David (David E.)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2009-04-29T14:49:35Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2009-04-29T14:49:35Z"]},{"key":"dc:date.issued","label":"Date","values":["2008"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Physics."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/45170"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2008.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Includes bibliographical references (p. 119-128)."]},{"key":"dc:description.abstract","label":"Abstract","values":["In this thesis, we describe the use of medical insurance claims data in three important areas of medicine. First, we develop expert- trained statistical models of quality of care based on variables derived from insurance claims. Such models can be used to identify patients who are receiving poor care so that interventions can be arranged to improve their care. Second, we develop an algorithm that utilizes claims data to perform post-marketing surveillance of drugs to detect previously unknown side effects. The algorithm performed strongly in several realistic simulation tests, detecting side effects a large fraction of the time while controlling the false detection rate. Lastly, we use insurance claims data to improve our understanding of the costs of care for patients who suffer from depression and a chronic disease."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Quality of care and drug surveillance : a data-driven perspective"]}]}],"canonical_facts":{"dc:contributor.advisor":["Dimitris J. Bertsimas."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Physics."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Physics."],"dc:creator":["Czerwinski, David (David E.)"],"dc:date.accessioned":["2009-04-29T14:49:35Z"],"dc:date.available":["2009-04-29T14:49:35Z"],"dc:date.issued":["2008"],"dc:description":["Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2008.","This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.","Includes bibliographical references (p. 119-128)."],"dc:description.abstract":["In this thesis, we describe the use of medical insurance claims data in three important areas of medicine. First, we develop expert- trained statistical models of quality of care based on variables derived from insurance claims. Such models can be used to identify patients who are receiving poor care so that interventions can be arranged to improve their care. Second, we develop an algorithm that utilizes claims data to perform post-marketing surveillance of drugs to detect previously unknown side effects. The algorithm performed strongly in several realistic simulation tests, detecting side effects a large fraction of the time while controlling the false detection rate. Lastly, we use insurance claims data to improve our understanding of the costs of care for patients who suffer from depression and a chronic disease."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/45170"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Physics."],"dc:title":["Quality of care and drug surveillance : a data-driven perspective"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:19Z"}